Problematising international placements as a site of intercultural learning

This paper theorises some of the learning outcomes of a three-year project concerning student learning in international social work placements in Malaysia. The problematic issue of promoting cultural and intercultural competence through such placements is examined, where overlapping hegemonies are discussed in terms of isomorphism of social work models, that of the nation state, together with those relating to professional values and knowledge, and the tyrannies of received ideas. A critical discussion of cultural competence as the rationale for international placements is discussed in terms of the development of the graduating social worker as a self-reflexive practitioner. The development of sustainable international partnerships able to support student placement and the issue of non-symmetrical reciprocation, typical of wide socio-economic differentials across global regions, is additionally discussed

Conic Multi-Task Classification

Traditionally, Multi-task Learning (MTL) models optimize the average of task-related objective functions, which is an intuitive approach and which we will be referring to as Average MTL. However, a more general framework, referred to as Conic MTL, can be formulated by considering conic combinations of the objective functions instead; in this framework, Average MTL arises as a special case, when all combination coefficients equal 1. Although the advantage of Conic MTL over Average MTL has been shown experimentally in previous works, no theoretical justification has been provided to date. In this paper, we derive a generalization bound for the Conic MTL method, and demonstrate that the tightest bound is not necessarily achieved, when all combination coefficients equal 1; hence, Average MTL may not always be the optimal choice, and it is important to consider Conic MTL. As a byproduct of the generalization bound, it also theoretically explains the good experimental results of previous relevant works. Finally, we propose a new Conic MTL model, whose conic combination coefficients minimize the generalization bound, instead of choosing them heuristically as has been done in previous methods. The rationale and advantage of our model is demonstrated and verified via a series of experiments by comparing with several other methods.Comment: Accepted by European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD)-201

Experimental Characterization of the Wettability of Coated and Uncoated Plates for Indirect Evaporative Cooling Systems

Indirect Evaporative Cooling (IEC) is a very promising technology to substitute and/or integrate traditional air conditioning systems, due to its ability to provide cooling capacity with limited power consumption. Literature studies proved that a higher wettability of the IEC plates corresponds to better performance of the system. In this work, wettability of three different surfaces used for IEC systems plates—uncoated aluminum alloy (AL), standard epoxy coating (STD), and a hydrophilic lacquer (HPHI)—is studied and characterized in terms of static and dynamic contact angles. The static contact angle resulted to be the lowest for the HPHI surface (average 69°), intermediate for the STD surface (average 75°), and the highest for the AL surface (average 89°). The analysis of the dynamic contact angles showed that their transient behavior is similar for all the surfaces, and the advancing and receding contact angles obtained are consistent with the results of the static analysis. These results will be useful as input parameters in models aimed at predicting the IEC system performance, also using computational fluid dynamics

Extending Explainable Boosting Machines to Scientific Image Data

As the deployment of computer vision technology becomes increasingly common in science, the need for explanations of the system and its output has become a focus of great concern. Driven by the pressing need for interpretable models in science, we propose the use of Explainable Boosting Machines (EBMs) for scientific image data. Inspired by an important application underpinning the development of quantum technologies, we apply EBMs to cold-atom soliton image data tabularized using Gabor Wavelet Transform-based techniques that preserve the spatial structure of the data. In doing so, we demonstrate the use of EBMs for image data for the first time and show that our approach provides explanations that are consistent with human intuition about the data.Comment: 7 pages, 2 figure

Milied it-tajjeb

Ġabra ta’ poeżiji u proża li tinkludi: Imħabba taħt siġra ta’ V. Caruana – L-isptar tal-Gwardamanġa ta’ P. Mattew – Lourdes – il-Belt tal-Madonna ta’ Ġużè Chetcuti – Ja iblah, ma temminx? ta’ John C. Friggieri – Ħolma ta’ A. Cremona – Il-Milied it-tajjeb ta’ Ġużè Borg Pantalleresco.peer-reviewe

The MUSE-Wide Survey: A first catalogue of 831 emission line galaxies

We present a first instalment of the MUSE-Wide survey, covering an area of 22.2 arcmin$^2$ (corresponding to $\sim$20% of the final survey) in the CANDELS/Deep area of the Chandra Deep Field South. We use the MUSE integral field spectrograph at the ESO VLT to conduct a full-area spectroscopic mapping at a depth of 1h exposure time per 1 arcmin$^2$ pointing. We searched for compact emission line objects using our newly developed LSDCat software based on a 3-D matched filtering approach, followed by interactive classification and redshift measurement of the sources. Our catalogue contains 831 distinct emission line galaxies with redshifts ranging from 0.04 to 6. Roughly one third (237) of the emission line sources are Lyman $\alpha$ emitting galaxies with $3 < z < 6$, only four of which had previously measured spectroscopic redshifts. At lower redshifts 351 galaxies are detected primarily by their [OII] emission line ($0.3 \lesssim z \lesssim 1.5$), 189 by their [OIII] line ($0.21 \lesssim z \lesssim 0.85$), and 46 by their H$\alpha$ line ($0.04 \lesssim z \lesssim 0.42$). Comparing our spectroscopic redshifts to photometric redshift estimates from the literature, we find excellent agreement for $z<1.5$ with a median $\Delta z$ of only $\sim 4 \times 10^{-4}$ and an outlier rate of 6%, however a significant systematic offset of $\Delta z = 0.26$ and an outlier rate of 23% for Ly$\alpha$ emitters at $z>3$. Together with the catalogue we also release 1D PSF-weighted extracted spectra and small 3D datacubes centred on each of the 831 sources.Comment: 24 pages, 14 figures, accepted for publication in A&A, data products are available for download from http://muse-vlt.eu/science/muse-wide-survey/ and later via the CD

Inflammatory mediators as biomarkers in brain disorders.

Neurodegenerative diseases such as Alzheimer, Parkinson, amyotrophic lateral sclerosis, and Huntington are incurable and debilitating conditions that result in progressive death of the neurons. The definite diagnosis of a neurodegenerative disorder is disadvantaged by the difficulty in obtaining biopsies and thereby to validate the clinical diagnosis with pathological results. Biomarkers are valuable indicators for detecting different phases of a disease such as prevention, early onset, treatment, progression, and monitoring the effect of pharmacological responses to a therapeutic intervention. Inflammation occurs in neurodegenerative diseases, and identification and validation of molecules involved in this process could be a strategy for finding new biomarkers. The ideal inflammatory biomarker needs to be easily measurable, must be reproducible, not subject to wide variation in the population, and unaffected by external factors. Our review summarizes the most important inflammation biomarkers currently available, whose specificity could be utilized for identifying and monitoring distinctive phases of different neurodegenerative diseases

Metformin increases APP expression and processing via oxidative stress, mitochondrial dysfunction and NF-κB activation: Use of insulin to attenuate metformin's effect

Clinical and experimental biomedical studies have shown Type 2 diabetes mellitus (T2DM) to be a risk factor for the development of Alzheimer's disease (AD). This study demonstrates the effect of metformin, a therapeutic biguanide administered for T2DM therapy, on β-amyloid precursor protein (APP) metabolism in in vitro, ex vivo and in vivo models. Furthermore, the protective role of insulin against metformin is also demonstrated. In LAN5 neuroblastoma cells, metformin increases APP and presenilin levels, proteins involved in AD. Overexpression of APP and presenilin 1 (Pres 1) increases APP cleavage and intracellular accumulation of β-amyloid peptide (Aβ), which, in turn, promotes aggregation of Aβ. In the experimental conditions utilized the drug causes oxidative stress, mitochondrial damage, decrease of Hexokinase-II levels and cytochrome C release, all of which lead to cell death. Several changes in oxidative stress-related genes following metformin treatment were detected by PCR arrays specific for the oxidative stress pathway. These effects of metformin were found to be antagonized by the addition of insulin, which reduced Aβ levels, oxidative stress, mitochondrial dysfunction and cell death. Similarly, antioxidant molecules, such as ferulic acid and curcumin, are able to revert metformin's effect. Comparable results were obtained using peripheral blood mononuclear cells. Finally, the involvement of NF-κB transcription factor in regulating APP and Pres 1 expression was investigated. Upon metformin treatment, NF-κB is activated and translocates from the cytoplasm to the nucleus, where it induces increased APP and Pres 1 transcription. The use of Bay11-7085 inhibitor suppressed the effect of metformin on APP and Pres 1 expression

Geomorphology of the seafloor north east of the Maltese Islands, Central Mediterranean

This paper presents a geomorphological map of the seafloor north east of the Maltese Islands (Central Mediterranean) at a scale of 1:50,000. The map was compiled following the integration, analysis and interpretation of several high-resolution seafloor bathymetry datasets. Several structural features, coastal and marine landforms and anthropogenic features have been mapped. Most of the mapped submerged landforms–including fluvial, gravity-induced and karst landforms–appear to have been formed during the sea-level lowstand of the last glacial cycle. The map provides valuable insights on the submerged landscape of the Maltese Islands and its evolution since the Last Glacial Maximum